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32-bit compilers emit, respectively: _f _g@4 @h@4 In the stdcall and fastcall mangling schemes, the function is encoded as _name@X and @name@X respectively, where X is the number of bytes, in decimal, of the argument(s) in the parameter list (including those passed in registers, for fastcall).
Polar performance can be improved with successive cancellation list decoding, but its usability in real applications is still questionable due to very poor implementation efficiencies caused by the iterative approach. [3] In October 2016, Huawei announced that it had achieved 27 Gbit/s in 5G field trial tests using polar codes for channel coding.
Algorithms developed for list decoding of several interesting code families have found interesting applications in computational complexity and the field of cryptography. Following is a sample list of applications outside of coding theory: Construction of hard-core predicates from one-way permutations. Predicting witnesses for NP-search problems.
There is a vast number of examples for block codes, many of which have a wide range of practical applications. The abstract definition of block codes is conceptually useful because it allows coding theorists, mathematicians, and computer scientists to study the limitations of all block codes in a unified way.
As with ideal observer decoding, a convention must be agreed to for non-unique decoding. The maximum likelihood decoding problem can also be modeled as an integer programming problem. [1] The maximum likelihood decoding algorithm is an instance of the "marginalize a product function" problem which is solved by applying the generalized ...
To decode an Elias gamma-coded integer: Read and count 0s from the stream until you reach the first 1. Call this count of zeroes N.; Considering the one that was reached to be the first digit of the integer, with a value of 2 N, read the remaining N digits of the integer.
One of the applications of locally decodable codes in complexity theory is hardness amplification. Using LDCs with polynomial codeword length and polylogarithmic query complexity, one can take a function : {,} {,} that is hard to solve on worst case inputs and design a function ′: {,} {,} that is hard to compute on average case inputs.
The basic idea of majority logic decoding is to build several checksums for each received code word element. Since each of the different checksums must all have the same value (i.e. the value of the message word element weight), we can use a majority logic decoding to decipher the value of the message word element.